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Artificial intelligence
Detect hallucinations for RAG-based systems
[ad_1] With the rise of generative AI and knowledge extraction in AI systems, Retrieval Augmented Generation (RAG) has become a prominent tool for enhancing…
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Machine Learning
Anomaly Detection Without Neural Networks: Isolation Forest, LOF, and Other Useful Techniques | by Jorge Martinez Santiago | May, 2025
[ad_1] When businesses and data scientists approach anomaly detection, many instinctively turn to deep learning models. Neural networks, autoencoders, and GANs have become go-to…
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Cybersecurity
GitHub upgrades tooling to help developers stop leaking secrets
[ad_1] “Previously, investing in secret scanning and push protection required purchasing a larger suite of security tools, which made fully investing unaffordable for many…
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Artificial intelligence
Bias Detection in LLM Outputs: Statistical Approaches
[ad_1] Bias Detection in LLM Outputs: Statistical ApproachesImage by Editor | Midjourney Natural language processing models including the wide variety of contemporary large language…
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Machine Learning
Custom Training Pipeline for Object Detection Models
[ad_1] What if you want to write the whole object detection training pipeline from scratch, so you can understand each step and be able…
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Machine Learning
PyOD 2: A Python Library for Outlier Detection Powered by LLMs | by Kuldeepkumawat | Mar, 2025
[ad_1] PyOD 2: AI-powered Python library for automated outlier detection with deep learning. Anomaly detection is a fundamental technique in data analysis that focuses…
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Cybersecurity
How AI-driven identify fraud is causing havoc
[ad_1] Deepfake fraud, synthetic identities, and AI-powered scams make identity theft harder to detect and prevent – here’s how to fight back 11 Feb…
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Cybersecurity
What is anomaly detection? Behavior-based analysis for cyber threats
[ad_1] Several use cases for anomaly detection don’t fit typical signature detections of typical industry-wide trends involving ransomware, data exfiltration, or command and control…
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